Our Mission

DATA‑INDUCTOR is a Finnish co‑innovation consortium designed to solve one of the biggest bottlenecks in modern drug development: the lack of human‑relevant, immunogenetically defined preclinical models.

“The major hurdle has been the lack of physiologically and immunologically appropriate models that effectively mimic human conditions.”

The project brings together leading Finnish universities, companies, and the Finnish Red Cross Blood Service to create integrated platforms for design, production, and testing of biologics and advanced therapies (ATMPs). The consortium leverages unique national assets such as immunogenotyped human samples, GLP‑validated in vitro models, and AI/ML‑driven multi‑omics integration.

Key goals include:

  • Developing human‑relevant in vitro models (e.g., immune‑organoids, tumor explants, HLA‑matched systems).
  • Creating Integrated Approaches for Testing and Assessment (IATA) to reach regulatory readiness.
  • Building AI‑enabled tools for drug design, target discovery, and toxicogenomics.
  • Validating new models and technologies for use by pharma and CROs.
  • Accelerating translation of EV‑based therapies, viral therapies, CAR‑immune cells, and other ATMPs.

The consortium aims to establish Finland as a global leader in biologics development by providing a unified ecosystem that supports the entire pipeline—from early design to GLP testing and regulatory alignment.

“DATA‑INDUCTOR will advance the field of drug development in Finland by establishing a cutting‑edge scientific, technological, methodological, and regulatory framework.”

 

Short Summary of Work Package Objectives

WP1 – Coordination and Commercial Development

Goal: Ensure smooth project execution, internal/external communication, market understanding, and preparation for future commercialization.

Key points:

  • Coordinate consortium activities and maintain communication.
  • Map partner value offerings and identify end‑user needs.
  • Conduct market research on regulatory consultancy and NAMs.
  • Build a roadmap for post‑project collaboration models.

Lead: Finnish Red Cross Blood Service

WP2 – Data‑Driven Machine Learning

Goal: Build AI/ML‑based infrastructure for drug design, target validation, and prediction of biological drug responses.

Key points:

  • Integrate multi‑omics datasets into a harmonized data environment.
  • Develop user‑friendly software tools for biologics design.
  • Create predictive AI models for efficacy and toxicity.
  • Combine omics, imaging, and molecular analytics.

Lead: FHAIVE, Tampere University

WP3 – Development of Human‑Relevant Models

Goal: Create, test, and validate advanced human‑based in vitro models for biologics and ATMPs.

Key points:

  • Build HLA‑matched and immunogenotyped models for cancer and immunology.
  • Integrate omics and imaging data to understand mechanisms of action.
  • Develop analytical tools for nanoparticles, viruses, EVs, and immune cells.
  • Test real drug candidates (e.g., EV therapies, CAR‑cells, oncolytic viruses).
  • Prepare SOPs and GLP validation for regulatory readiness.

Lead: University of Turku, Co-lead FHAIVE Tampere University